An Approach Using Elman Neural Network to Predict the Model for a Nonlinear Process

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Provided by: International Journal of Research in Electronics and Computer Engineering (IJRECE)
Topic: Networking
Format: PDF
Most of the industries such as chemical, textile, paper and pharmaceutical use non-linear processes for their production. Generally, the system dynamics of non-linear processes are complex. Due to such complexities, difficulties arise in controlling the plant's operations in desired fashion. In order to ensure desired productivity and safe operation of the plant, it is mandatory to govern the process variables effectively. To achieve such an operation, system identification of the process is essential. But the major problems with system identification is maintaining the stability and observing its dynamic behavior.
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